slideMerge            package:arrayMagic            R Documentation

_A_v_e_r_a_g_i_n_g _o_f _t_w_o _c_o_l_o_u_r _m_i_c_r_o_a_r_r_a_y _r_e_p_l_i_c_a_s

_D_e_s_c_r_i_p_t_i_o_n:

     The mean of the expression values is calculated separately for
     each channel. If no 'se.exprs' values are given in
     'exprSetRGObject', 'se.exprs' is set to the standard deviation of
     the expression values (which is possibly 'NA'). If available it is
     set to the root-mean-square or the mean of the given 'se.exprs'
     values depending on the argument 'seExprsHandling'. The
     root-mean-square can be useful if the  'se.exprs' values are
     estimated standard deviations based on the same number
     observations taken from identical distributions.

_U_s_a_g_e:

     slideMerge(exprSetRGObject, slideMergeColumn, sampleAnnotationColumns, seExprsHandling="rootMeanSquare", verbose=TRUE)

_A_r_g_u_m_e_n_t_s:

exprSetRGObject: object of class 'exprSetRG'; required; default missing

slideMergeColumn: character string specifying the variable of the
          'phenoData' object of the 'exprSetRGObject', which is used to
          determine replicas; required; default missing

sampleAnnotationColumns: vector of character strings; optional; default
          missing. A vector which contains all 'phenoData' variables
          relevant for further analysis. The 'phenoData'-annotation
          should be consistent for replicas. By default the argument
          'sampleAnnotationColumns' is missing and all 'phenoData'
          variables are used.

seExprsHandling: character string; either "rootMeanSquare" or "mean";
          required; default "rootMeanSquare" 

 verbose: logical; required; default: 'TRUE' 

_D_e_t_a_i_l_s:

_V_a_l_u_e:

     object of class 'exprSetRG-class', i.e. the "merged"
     'exprSetRGObject'

_A_u_t_h_o_r(_s):

     Andreas Buness <a.buness@dkfz.de>

_S_e_e _A_l_s_o:

     'spotMerge', 'exprSetRG-class'

_E_x_a_m_p_l_e_s:

       indGreen=1:2
       indRed=3:4
       channels <- matrix( c(indGreen,indRed), nrow=length(indGreen), byrow=FALSE )
       colnames(channels) <- c("green","red")
       exprsMatrix <- matrix(rep(1:10,4),nrow=10,ncol=4,byrow=FALSE)
       phenoMatrix <- matrix(c(c(1,2),c(3,3),c(5,5)),nrow=2,ncol=3,byrow=FALSE)
       colnames(phenoMatrix) <- c("one","two","usedForMerge")
       phenoMatrix <- rbind(phenoMatrix,phenoMatrix)
       eSA <- new("exprSetRG", exprs=exprsMatrix, phenoData=
                  new("phenoData", pData=data.frame(phenoMatrix),
                      varLabels=as.list(colnames(phenoMatrix))),
                  channels=channels)
       eSM <- slideMerge(exprSetRGObject=eSA, slideMergeColumn="usedForMerge")
       eSAOne <- slideSubset(eSA,j=c(1))
       stopifnot( all(exprs(eSAOne) == exprs(eSM) ))
       stopifnot( all( se.exprs(eSM) == 0 ) )

      

             

